We further study how prompt length and training data size affects the performance of learned prompt by training on seen classes and testing on unseen classes. The results are shown in tab:promthyper, and the best performance is achieved when we use 32 samples for each category, in either prompt length of 16 or 32, and more training samples will degrade the performance, we speculate that more samples may lead over-fitting issue, which is also reported by other prompt learning attempts [1]}.
